单晶叶片材料蠕变试验研究

针对单晶材料涡轮叶片的蠕变计算分析的需要,对我国自行设计的单晶材料DD3进行蠕变试验,根据试验结果提出了进行曲线拟合的方法,并与有限元法计算相结合,对拟合出的蠕变律常数进行了修正,提出了较好符合试验曲线的较精确的Norton蠕变律有关常数A、n和p值,满足了单晶叶片非线性有限元蠕变分析的要求.     

用CBN刀具高速切削灰铸铁的试验研究

研究了CBN刀具高速切削灰铸铁时的刀具前、后刀面磨损、耐用度以及富氧气氛对切削性能的影响,所用的灰铸铁具有不同的铁素体、珠光体比例,最高切削速度达1＇100 m/min.研究表明Amborite刀具的刀尖磨损略大于BZN6000刀具,在较低速度下加工以铁素体为主的灰铸铁时更容易发生月牙洼磨损;BZN6000刀具以700 m/min的切削速度加工铁素体含量较高的灰铸铁时耐用度较高,Amborite刀具的耐用度随切削速度而升高;在富氧气氛中切削可以减轻刀具磨损,这一效果对BZN6000刀具更为显著.文章中对这些现象的原因进行了讨论.     

S-08钢真空熔模精密铸造工艺研究

通过工艺试验和系统分析,研究出一套用真空感应铸造炉生产S-08钢铸件的工艺方法,解决S—08钢真空熔模精密铸造过程中的关键工艺技术问题,使S-08钢铸造的液氧／煤油发动机低压壳体、氧主阀下壳体等关键铸件满足高压、高冲击的负荷指标。     

平面叶栅尾流板开孔率对跨声速涡轮叶栅流道影响的数值分析

跨声速平面叶栅风洞中通常通过尾流板来改善平面叶栅周期性,针对尾流板的设计需求,利用数值模拟的方法,研究了尾流板在15%、30%、50%开孔率下对实验叶栅的影响。数值分析结果表明:叶栅尾缘激波在自由边界上反射后,返回到叶栅通道中,破坏了叶栅通道的周期性;开槽尾流板减少了反射波对叶栅通道的影响,减弱叶栅尾缘激波的反射波强度,在某特定情况下能使反射波变成膨胀波,从而提高了叶栅通道周期性;尾流板开孔率为15%时能极大地改善平面叶栅通道的周期性,相对于开孔率为50%时叶栅的周期性误差降低约16.43%。      

空间科学任务协同设计论证平台

空间科学任务协同设计论证存在设计方案耦合强,数据一致性差,数据变更难,数据与流程脱节等问题.为了解决上述问题,建立了典型空间科学任务的多层数字化模型;采用图形化方式对论证流程进行建模,并建立流程与数据的映射关系;通过共享数据池的方式为多岗位用户提供多方案数据协同机制;采用消息总线对数据变更进行及时提醒;利用方案依赖关系矩阵来判别方案耦合关系,最终自动合并任务总体设计方案.作为一个分布式平台,空间科学任务协同设计平台采用Eclipse RCP和Spring技术架构,整合了Hibernate、工作流Activiti5等中间件,提供统一门户,支持多岗位、多任务、多方案、多版本的管理能力,提供论证流程监控、数据协同交互等功能.结合某空间科学任务论证验证了该平台的有效性.      

民用飞机维修类技术出版物符合性验证方法

通过分析民用飞机维修类技术出版物内容的特点,确定技术出版物适航验证要求。提出维修类技术出版物符合性验证方法、流程和管理要求。利用模糊综合评判方法进行定量评估,解决了民用飞机适航认证维修类技术出版物符合性验证无据可依的问题。     

基于CAIV的导弹低成本保障性指标论证技术

利用CAIV技术分别建立反舰导弹的作战效能模型和总拥有费用模型,并以权衡空间为约束条件,以费用最低为目标,建立保障性指标权衡优化模型。该方法可以为导弹武器装备保障性指标论证工作提供必要的理论基础和技术支持。     

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.     

Effects of wing flexibility on aerodynamic performance of an aircraft model

The low-speed wind tunnel experiment is carried out on a simplified aircraft model to explore the influence of wing flexibility on the aircraft aerodynamic performance. The investigation involves the measurements of force, membrane deformation and velocity field at Reynolds number of 5.4 × 10⁴–1.1 × 10⁵. In the lift curves, two peaks are observed. The first peak, corresponding to the stall, is sensitive to the wing flexibility much more than the second peak, which nearly keeps constant. For the optimal case, in comparison with the rigid wing model, the delayed stall of nearly 5° is achieved, and the relative lift increment is about 90%. It is revealed that the lift enhanced region corresponds to the larger deformation and stronger vibration, which leads to stronger flow mixing near the flexible wing surface. Thereby, the leading-edge separation is suppressed, and the aerodynamic performance is improved significantly. Furthermore, the effects of sweep angle and Reynolds number on the aerodynamic characteristics of flexible wing are also presented.     

基于高斯过程的机器人自适应抓取策略

在机器人抓取作业时,目标物体的位姿经常发生变化。为了使机器人在运动过程中能够适应物体的位姿变化,提出了一种基于高斯过程的机器人自适应抓取策略。该方法建立了从观测空间到关节空间的映射,使机器人从样本中学习,省去了机器人视觉系统的标定和逆运动学求解。首先,拖动机器人抓取物体,记录物体的观测变量和机器人的关节角度;然后,利用记录的样本训练高斯过程模型,实现观测变量和关节角度的关联;最后,当得到新的观测变量时,通过训练的高斯过程模型得到机器人的关节角度。经过训练后,UR3机器人成功抓取了物体。